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AB ai-test-platform

This skill should be used when developing or using an AI-powered automated testing platform based on LangChain+DeepSeek. It implements intelligent test case generation, automated script execution (API/UI), test reporting, and authorization management for internal company use.

ClawHub Agent Skills author: yontlly v1.0.0 MIT-0 75 files body ≈ 2 860 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 66/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, running it twice

IntegrationInfrastructureData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
92
Quality 40%
94
Run on models
none yet
Process rating
B
66/100
Nearly there
Inputs and preconditions w 11
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 4

    ✓ No critical or high findings

    Medium and low: 4
    • medium Dangerous commands cmd-privilege deploy/部署文档.md:230
      Privilege escalation / world-writable permissions
      echo "deb [arch=amd64 signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /de
    • low Dangerous commands cmd-background-process deploy/部署文档.md:125
      Starts a background / autostarted process
      sudo systemctl enable mysql
    • low Dangerous commands cmd-background-process deploy/部署文档.md:238
      Starts a background / autostarted process
      sudo systemctl enable docker
    • low Secrets in code secret-password-literal project/backend/app/models/system.py:20
      Hard-coded password / key literal (may be an example)
      api_key = Column(String(255), comment="API密钥（加密存储）")

    Files scanned: 75. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 66/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 11 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 130 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2860 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 15 top-level sections: this looks like several domains in one skill

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 276: enough signal without eating the budget
    • +4Structure: 40 headings
    • +3Step-by-step instructions: 130 items
    • +3Output format is stated explicitly
    • +4Has examples (12 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.

    External checks

    ClawHub: suspicious
    The skill matches an internal AI testing platform, but it gives broad high-impact authority with weak scoping and unclear data-boundary protections.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026